Chinese-origin AI models jumped from 4.5% to 63% of enterprise use in one year No law defines illegal AI distillation, letting extraction pass as ordinary training use Closing that legal gap, not banning open models, protects both competition and security

Keith Lee*

AI access is common; implementation creates value Deeper AI use carries a stronger market signal Future advantage will depend on workflow redesign and outcomes In the first four months of 2024, weekly AI token consumption on one major

Keith Lee*

GPT-5.6 Sol breached Hugging Face The breach strengthened OpenAI’s capability narrative Zero-day knowledge sharing is becoming dangerous A rogue AI agent broke into another company's servers this month and the company that b

AI access helps only when workers can recognise system failure Task-specific learning can spread that supervisory capacity Delay will widen the divide between AI Haves and AI Have-Nots In a field experiment with 758 consultants,

Keith Lee*

Keith Lee*

Keith Lee*

AI is not yet a universal substitute for human labor.

Keith Lee*

Keith Lee*

AI can create task-specific “superhuman productivity,” sharply compressing the time required for some knowledge work without implying that one person can replace ten complete jobs he fiscal risk is less an immediate collapse of government revenue than a gradual shift from broadly taxed labour income toward concentrated profits, capital income and economic rents Because those gains are more mobile across borders than payroll, governments will need stronger capital-income taxation, better measurement and international coordination rather than a blunt tax on AI itself

AI can accelerate biological research, diagnosis, prevention and care, raising the prospect of longer and healthier lives Its nearer-term labour effect may be unequal augmentation: a small group becomes dramatically more productive while others lose bargaining power or move into lower-quality work Because work, income, wealth and access shape health, AI could widen longevity inequality unless its productivity and medical dividends are deliberately shared

Adaptive AI systems partly create the data from which they learn Long memory can preserve hallucinations as easily as valid information Causal identification must become a distinct layer of AI architecture Artificial-intelligence systems are increasingly

Digital markets convert previously unpriced expectations into observable data LLMs connect news, discussion, and policy language to real-time price movements Prediction markets may create measurable signals for political, scientific, and social risk

Educational systems train habits of thought, not only knowledge Examination success does not necessarily produce analytical independence SIAI seeks to replace answer-oriented learning with causal inquiry A recent study published

Prediction markets as laboratories for uncertainty, sentiment, and regime change Student research converted into models, data systems, and institutional capability SIAI Labs as the bridge from academic work to a research-driven service

Human feedback does not eliminate endogeneity or causal confusion Lagged observations can transmit error as easily as information Econometric identification should become part of advanced AI training There is a phrase frequently used in economics: “econo

AI is moving from a low-cost software experiment to a metered production input whose bill rises with use Cheaper tokens do not guarantee lower spending: agents, context, tools, and repeated inference can expand consumption faster than unit prices fall The automation threshold is crossed when AI becomes cheaper, more predictable, and sufficiently reliable at the task level—not merely when a model can perform the task